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Fluoroquinolones (FQ) form the backbone in experimental treatment regimens against drug-susceptible tuberculosis. However, little is known on whether the genetic variation present in natural populations of Mycobacterium tuberculosis (Mtb) affects the evolution of FQ-resistance (FQ-R). To investigate this question, we used nine genetically distinct drug-susceptible clinical isolates of Mtb and measured their frequency of resistance to the FQ ofloxacin (OFX) in vitro. We found that the Mtb genetic background led to differences in the frequency of OFX-resistance (OFX-R) that spanned two orders of magnitude and substantially modulated the observed mutational profiles for OFX-R. Further, in vitro assays showed that the genetic background also influenced the minimum inhibitory concentration and the fitness effect conferred by a given OFX-R mutation. To test the clinical relevance of our in vitro work, we surveyed the mutational profile for FQ-R in publicly available genomic sequences from clinical Mtb isolates, and found substantial Mtb lineage-dependent variability. Comparison of the clinical and the in vitro mutational profiles for FQ-R showed that 51% and 39% of the variability in the clinical frequency of FQ-R gyrA mutation events in Lineage 2 and Lineage 4 strains, respectively, can be attributed to how Mtb evolves FQ-R in vitro. As the Mtb genetic background strongly influenced the evolution of FQ-R in vitro, we conclude that the genetic background of Mtb also impacts the evolution of FQ-R in the clinic.

Background. Whole-genome sequencing (WGS) is increasingly used in molecular-epidemiological investigations of bacterial pathogens, despite cost- and time-intensive analyses. We combined strain-specific single-nucleotide polymorphism (SNP) typing and targeted WGS to investigate a tuberculosis cluster spanning 21 years in Bern, Switzerland. Methods. On the basis of genome sequences of 3 historical outbreak Mycobacterium tuberculosis isolates, we developed a strain-specific SNP-typing assay to identify further cases. We screened 1642 patient isolates and performed WGS on all identified cluster isolates. We extracted SNPs to construct genomic networks. Clinical and social data were retrospectively collected. Results. We identified 68 patients associated with the outbreak strain. Most received a tuberculosis diagnosis in 1991-1995, but cases were observed until 2011. Two thirds were homeless and/or substance abusers. Targeted WGS revealed 133 variable SNP positions among outbreak isolates. Genomic network analyses suggested a single origin of the outbreak, with subsequent division into 3 subclusters. Isolates from patients with confirmed epidemiological links differed by 0-11 SNPs. Conclusions. Strain-specific SNP genotyping allowed rapid and inexpensive identification of M. tuberculosis outbreak isolates in a population-based strain collection. Subsequent targeted WGS provided detailed insights into transmission dynamics. This combined approach could be applied to track bacterial pathogens in real time and at high resolution